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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

ABSTRACT: To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.Eighty-five rectal cancer patients underwent preoperative CRT. 18F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate models were built combining the obtained parameters. Final models were calculated on the data combination with the highest AUC.Twenty-two patients (26%) achieved ypT0-1N0 response. 18F-FDG PET/CT had worse predictive performance than DWI and T2-volumetry (AUC 0.61±0.04, 0.72±0.03, and 0.72±0.02, respectively). Combining all imaging parameters increased the AUC to 0.81±0.03. Adding cytokines or gene expression did not improve the AUC (AUC of 0.72±0.06 and 0.79±0.04 respectively). Final models combining 18F-FDG PET/CT, DWI, and T2-weighted volumetry at all TPs and using only TP1 and TP3, allowed ypT0-1N0 prediction with a 75% sensitivity, 94% specificity and PPV of 80%.Combining 18F-FDG PET/CT, DWI, and T2-weighted MRI volumetry obtained before CRT and prior to surgery may help physicians in selecting rectal cancer patients for organ-preservation.

SUBMITTER: Joye I

PROVIDER: S-EPMC5641595 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

Joye Ines I Debucquoy Annelies A Deroose Christophe M CM Vandecaveye Vincent V Cutsem Eric Van EV Wolthuis Albert A D'Hoore André A Sagaert Xavier X Zhou Mu M Gevaert Olivier O Haustermans Karin K

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 20170621 1

<h4>Background and purpose</h4>To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.<h4>Material and methods</h4>Eighty-five rectal cancer patients underwent preoperative CRT. <sup>18</sup>F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate ...[more]

PMID: 28647399

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Project description:Neoadjuvant chemoradiotherapy (nCRT) following surgery significantly improves the survival rate of patients with rectal cancer. However, nCRT is associated with significant adverse symptoms and high medical costs. Therefore, it is important to investigate potential biomarkers for the prediction of the response to nCRT in patients with rectal cancer. The present study identified candidate biomarkers for predicting a complete response (CR) to nCRT in patients with rectal cancer and investigated the associated mechanisms. Microarray data (accession no. GSE29298) was downloaded from the Gene Expression Omnibus database. Differentially expressed microRNAs (miRNAs/miR) were screened between the pathological CR (pCR) group and no pCR (incomplete response) group. miRNA target genes were predicted using the miRWalk 2.0 online tool and subjected to Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Furthermore, a miRNA co‑regulatory network was constructed and disease‑associated genes were predicted. The results demonstrated that a total of 36 upregulated and 5 downregulated miRNAs were identified between the two groups. Among these differentially expressed miRNAs, miR‑548c‑5p, miR‑548d‑5p and miR‑663a were significantly associated with a CR to nCRT. The co‑regulatory network and pathway analysis indicated that miR‑548c‑5p and miR‑548d‑5p may function together through stem cell pluripotency and ubiquitin‑mediated proteolysis signaling pathways. Furthermore, the prediction of disease‑associated genes demonstrated that miR‑548c‑5p/miR‑548d‑5p and miR‑663a may regulate genes associated with rectal cancer, including mutated in colorectal cancers (MCC) and adenomatous polyposis coli (APC), and colorectal neoplasms, including interleukin‑6 signal transducer (IL6ST), cell cycle checkpoint kinase 2 (CHEK2), marker of proliferation Ki‑67 (MKI67), cadherin 7 (CDH7), calreticulin (CALR) and transforming growth factor β1 (TGFB1). Therefore, miR‑548c‑5p, miR‑548d‑5p and miR‑663a are promising candidate biomarkers for predicting a CR to nCRT. miR‑548c‑5p/miR‑548d‑5p may be associated with a CR by regulating IL6ST, CHEK2, MKI67 and MCC. In addition, it may function through the pluripotency of stem cells and ubiquitin‑mediated proteolysis signaling pathways. miR‑663a may be associated with a CR to nCRT by targeting CDH7, CALR, APC and TGFβ1. Thus, the miRNA biomarkers investigated in the present study may represent novel therapeutic targets for the prediction and eventual improvement of the response to nCRT in patients with rectal cancer.

Project description:Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.

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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

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